Abstract
Much has been made about the difficulties students have in transferring their learning from one context to another. We suggest that students learning from examples use ‘imitation’, a subtype of analogical problem solving (APS). Whereas APS involves manipulating a mental representation, imitation involves mapping the surface features of a source example to a target problem and no assumptions are made about what a student ‘knows’. Often imitating a ‘close variant’ of a source problem is likely to be relatively successful; however, trying to solve a ‘distant variant’ by imitating an example creates difficulties in mapping values and adapting the source example to the target. In this paper we argue that some students' inability to transfer their learning is very often due to the teaching material rather than any ‘failure’ on the part of the student. To this end, we have developed an interpretation theory based on the proportional analogy framework (a:b::c:d) which can be applied to text analysis. The theory is demonstrated using examples taken mainly from computer programming textbooks.
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References
Adelson, B. (1981). Problem solving and the development of abstract categories in programming languages. Memory & Cognition 9: 422–433.
Adelson, B. (1984). When novices surpass experts: The difficulty of a task may increase with expertise. Journal of Experimental Psychology: Learning, Memory, & Cognition 10: 483–495.
Anderson, J. R. (1983). The Architecture of Cognition. Cambridge, MA: Harvard University Press.
Anderson, J. R., Farrell, R. & Sauers, R. (1984). Learning to program in LISP. Cognitive Science 8: 87–129.
Anderson, J. R. & Thompson, R. (1989). Use of an analogy in a production system architecture, in S. Vosniadou & A. Ortony, eds., Similarity and Analogical Reasoning (pp. 267–297). London: Cambridge University Press.
Bassok, M. (1990). Transfer of domain-specific problem solving procedures. Journal of Experimental Psychology Learning, Memory, and Cognition 16(3): 522–533.
Beck, I. L. & McKeown, M. G. (1989). Expository text for young readers: The issue of coherence, in L. B. Resnick, eds., Knowing, Learning, and Instruction: Essays in Honor of Robert Glaser (pp. 47–66). Hillsdale, NJ: Erlbaum.
Bonar, J. & Soloway, E. (1985). Preprogramming knowledge: A major source of misconceptions in novice programmers. Human-Computer Interaction 1(2): 133–161.
Britton, B. K., Van Dusen, L., Glynn, S. M. & Hemphill, D. (1990). The impact of inferences on instructional text, in A. C. Graesser & G. H. Bower, eds., The Psychology of Learning and Motivation: Inferences and Text Comprehension (pp. 53–70). London: Academic Press.
Britton, B. K., Van Dusen, L., Gulgoz, S. & Glynn, S. M. (1989). Instructional texts rewritten by five expert teams: Revisions and retention improvements. Journal of Educational Psychology 81(2): 226–239.
Butterfield, E. C. (1988). On solving the transfer problem, in M. M. Gruneberg, P. E. Morris & R. N. Sykes, eds., Practical Aspects of Memory: Current Research and Issues. Chichester: Wiley.
Catrambone, R. (1990). Specific versus general procedures in instructions. Human Computer Interaction 5: 49–93.
Catrambone, R. & Holyoak, K. J. (1989). Overcoming contextual limitations on problem-solving transfer, Journal of Experimental Psychology: Learning, Memory, & Cognition 15(6): 1147–1156.
Chi, M. T., Bassok, M., Lewis, M. W., Reimann, P. & Glaser, R. (1989). Self-explanations: How students study and use examples in learning to solve problems. Cognitive Science 13: 145–182.
Conway, M. & Kahney, H. (1987). Transfer of learning in inference problems, in J. Hallam & C. Mellish, eds., Advances in Artificial Intelligence. Chichester: John Wiley.
Cooper, G. & Sweller, J. (1987). Effects of schema acquisition and rule automation on mathematical problem solving transfer. Journal of Educational Psychology 79(4): 347–362.
Duncker, K. (1945). On problem solving. Psychological Monographs 58 (Whole no. 270).
Ehrlich, K. & Soloway, E. (1984). An empirical investigation of tacit plan knowledge in programming, in J. C. Thomas & M. L. Schneider, eds., Human Factors in Computer Systems. Norwood, NJ: Ablex.
Eisenstadt, M. (1978/1983). Units 3–4, Artificial Intelligence Project. Milton Keynes: The Open University.
Gentner, D. & Gentner, D. R. (1983). Flowing waters or teeming crowds: mental models of electricity, in D. Gentner & A. L. Stevens, eds., Mental Models. Hillsdale, N.J.: Lawrence Erlbaum Associates.
Gentner, D. & Stevens, A. L. (1983). Mental Models. Hillsdale, NJ: Lawrence Erlbaum Associates.
Gick, M. L. & Holyoak, K. J. (1980). Analogical problem solving. Cognitive Psychology 12: 306–356.
Gick, M. L. & Holyoak, K. J. (1983). Schema induction and analogical transfer. Cognitive Psychology 15: 1–38.
Glaser, R. & Bassok, M. (1989). Learning theory and the study of instruction, in M. R. Rosenzweig & L. W. Poerter, eds., Annual Review of Psychology (pp. 631–666). Palo Alto, CA: Annual Reviews, Inc.
Graesser, A. C. & Bower, G. H. (ed.) (1990). The Psychology of Learning and Motivation: Inferences and Text Comprehension. London: Academic Press.
Green, A. J. K. & Gilhooly, K. J. (1990). Statistical computing: Individual differences in learning at macroscopic and microscopic levels, in K. J. Gilhooly, M. T. G. Keane, R. H. Logie & G. Erdos, eds., Lines of Thinking. Chichester: Wiley.
Hasemer, T. & Domingue, J. (1989). Common Lisp Programming for Artificial Intelligence. Wokingham: Addison-Wesley.
Hiebert, J. (ed.) (1986). Conceptual and Procedural Knowledge: The Case of Mathematics. Hillsdale, NJ: Erlbaum.
Holland, J. H., Holyoak, K. J., Nisbett, R. E. & Thagard, P. R. (1986). Induction: Processes of Inference, Learning and Discovery. Cambridge, MA: MIT Press.
Holyoak, K. J. (1984). Analogical thinking and human intelligence, in R. J. Sternberg, eds., Advances in the Psychology of Human Intelligence. Hillsdale, NJ: Erlbaum.
Holyoak, K. J. (1985). The Pragmatics of Analogical Transfer. New York; Academic Press.
Holyoak, K. J. & Koh, K. (1987). Surface and structural similarity in analogical transfer. Memory and Cognition 15(4): 332–340.
Holyoak, K. J. & Thagard, P. R. (1989). A computational model of analogical problem solving, in S. Vosniadou & A. Ortony, eds., Similarity and Analogical Reasoning. London: Cambridge University Press.
Issing, L. J., Hannemann, J. & Haack, J. (1989). Visualization by pictorial analogies in understanding expository text, in H. Mandl & J. R. Levin, eds., Knowledge Acquisition from Text and Picture (pp. 195–214). Amsterdam: Elsevier.
Kahney, H. (1982). An In-depth Study of the Cognitive Behaviour of Novice Programmes (HCRL Technical Report No. 5). The Open University.
Kieras, D. E. (1985). Thematic processes in the comprehension of technical prose, in B. K. Britton & J. B. Black, eds., Understanding Expository Text: A Theoretical and Practical Handbook for Analyzing Explanatory Text (pp. 89–107). Hillsdale, NJ: Erlbaum.
Kinstch, W. (1986). Learning from text. Cognition and Instruction 3(2): 87–108.
Kintsch, W. (1988). The role of knowledge in discourse-comprehension: a construction-integration model. Psychological Review 95: 163–182.
Kintsch, W. & Greeno, J. G. (1985). Understanding and solving word arithmetic problems. Psychological Review 92(1): 109–129.
Martindale, M. J. (1993). Mental models and text schemas: Why computer based tutorials should be considered a communication medium. Journal of Computer-Based Instruction 20(4): 107–112.
Mayer, R. E. (1989). The Psychology of How Novices Learn Computer Programming. Hillsdale, NJ: erlbaum.
Novick, L. R. (1988). Analogical transfer, program similarity, and expertise. Journal of Experimental Psychology Learning, Memory, and Cognition 14(3): 510–520.
Novick, L. R. & Holyoak, K. J. (1991). Mathematical problem solving by analogy. Journal of Experimental Psychology: Learning, Memory, and Cognition 17(3): 398–415.
Owen, E. & Sweller, J. (1985). What do students learn while solving mathematics problems? Journal of Educational Psychology 77(3): 272–284.
Rayner, D. (1990). Complete Mathematics for G.C.S.E. and Standard Grade. Oxford: Oxford University Press.
Reed, S. K. & Bolstad, C. A. (1991). Use of examples and procedures in problem solving. Journal of Experimental Psychology: Learning, Memory, and Cognition 17: 753–766.
Reed, S. K., Dempster, A. & Ettinger, M. (1985). Usefulness of analogous solutions for solving algebra word problems. Journal of Experimental Psychology Learning, Memory, and Cognition 11(1): 106–125.
Reed, S. K., Ernst, G. W. & Banerji, R. (1974). The role of analogy in transfer between similar problem states. Cognitive Psychology 6: 436–450.
Reed, S. K. & Ettinger, M. (1987). Usefulness of tables for solving word problems. Cognition and Instruction 4(1): 43–58.
Resnick, L. B. (eds) (1989). Knowing, Learning, and Instruction: Essays in Honor of Robert Glaser (pp. 1–24). Hillsdale, NJ: Erlbaum.
Robertson, W. C. (1990). Detection of cognitive structure with protocol data: Predicting performance on physics transfer problems. Cognitive Science 14(2): 253–280.
Robertson, S. I. (1994). Problem Solving from Textbook Examples (Technical Report No. 114). H.C.R.L., The Open University.
Robertson, S. I. & Kahney, H. (1994). Computational models of analogical problem solving: The pitfalls. FLAIRS, '94. Pensacola Beach, Florida.
Robertson, S. I. & Kahney, H. (1993). How do Examples Help Solvers Solve Problems? An Interpretation Theory for Text Analysis (Technical Report No. 96). HCRL, The Open University.
Ross, B. H. (1989). Distinguishing types of superficial similarities. Different effects on the access and use of earlier problems. Journal of Experimental Psychology: Learning Memory, & Cognition 14: 510–520.
Spearman, C. (1923). The Nature of “Intelligence” and the Principles of Cognition. London: Macmillan.
Sternberg, R. J. (1977). Intelligence, Information Processing and Analogical Reasoning: The Componential Analysis of Human Abilities. Hillsdale, NJ: Lawrence Erlbaum Associates.
Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive Science 12: 257–285.
Sweller, J. & Cooper, G. A. (1985). The use of worked examples as a substitute for problem solving in learning algebra Cognition and Instruction 2: 59–89.
Sweller, J., Mawer, R. F. & Ward, M. R. (1983). Development of expertise in mathematical problem solving. Journal of Experimental Psychology: General 112: 639–661.
Van Lehn, K. & Jones, R. M. (1993). Better learners use analogical problem solving sparingly, in P. E. Utgoff, ed., Machine Learning: Proceedings of the tenth annual conference. San Mateo, CA: Morgan Kaufman.
Winston, P. H. & Horn, B. K. P. (1981). LISP. Reading, MA: Addison-Wesley.
Winston, P. H. & Horn, B. K. P. (1984). LISP. Second Edition. Reading, MA: Addison-Wesley.
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Robertson, I., Kahney, H. The use of examples in expository texts: Outline of an interpretation theory for text analysis. Instr Sci 24, 93–123 (1996). https://doi.org/10.1007/BF00120485
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DOI: https://doi.org/10.1007/BF00120485